Abstract
Traffic incidents such as crashes, vehicle breakdowns, and hazards impact traffic speeds and induce congestion. Recognizing the factors that influence the frequency of these traffic incidents is helpful in proposing countermeasures. There have been several studies on evaluating crash frequencies. However, research on other incident types is sparse. The main objective of this research is to identify critical variables that affect the number of reported vehicle breakdowns. A traffic incident dataset covering 4.5 years (January 2012 to June 2016) in the Australian state of New South Wales (NSW) was arranged in a panel data format, consisting of monthly reported vehicle breakdowns in 28 SA4s (Statistical Area Level 4) in NSW. The impact of different independent variables on the number of breakdowns reported in each month–SA4 observation is captured using a random-effect negative binomial regression model. The results indicate that increases in population density, the number of registered vehicles, the number of public holidays, average temperature, the percentage of heavy vehicles, and percentage of white-collared jobs in an area increase the number of breakdowns. On the other hand, an increase in the percentage of unrestricted driving licenses and families with children, number of school holidays, and average rainfall decrease the breakdown frequency. The insights offered in this study contribute to a complete picture of the relevant factors that can be used by transport authorities, vehicle manufacturers, sellers, roadside assistance companies, and mechanics to better manage the impact of vehicle breakdowns.
Highlights
Investigating ways to reduce the impacts of road congestion is an increasingly important challenge as vehicle ownership and population increase across the world
The current study addresses the gap in the literature thanks to a more comprehensive, long-baseline dataset of unplanned incidents that includes on-road breakdowns across the state of New South Wales (NSW), Australia
The elasticity indicates that as the logarithm of population density increases by 1%, the total number of breakdowns in NSW increases by 1.33% when the remaining variables are equal to the original values
Summary
Investigating ways to reduce the impacts of road congestion is an increasingly important challenge as vehicle ownership and population increase across the world. Traffic congestion is divided into two categories, namely recurrent and non-recurrent [1]. Recurrent congestion is caused by demand chronically exceeding road capacity, and non-recurrent congestion is caused by random events, such as traffic incidents, adverse weather, and hazards [2]. Non-recurrent traffic congestion is non-trivial, and it was found to account for up to 60% of total congestion [3]. As the critical source of non-recurrent congestion, a traffic incident is defined as a non-recurring event that causes a reduction of roadway capacity or an abnormal increase in demand [4]. Breakdowns, police stops, and hazards are some examples of the non-planned incidents that impact the typical traffic conditions. Commuters tend to show varying behaviors, such as risk aversion, risk neutrality, and risk seeking [6]
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